Generative AI for Observability: Automating Root Cause Analysis in Modern IT Systems
As modern IT systems grow in complexity, the traditional approaches to root cause analysis (RCA) are proving too slow, too manual, and too reactive. Observability platforms produce a flood of logs, metrics, and traces—but transforming that raw telemetry into actionable insights remains a major challenge. This session explores how Generative AI can be used to automate RCA by understanding system behavior, correlating disparate signals, and generating human-readable incident reports. By leveraging pre-trained language models and retrieval-augmented architectures, AI agents can now analyze incidents contextually and assist engineers in identifying probable root causes—dramatically reducing mean time to resolution (MTTR). Key takeaways: How to design observability workflows enhanced with generative reasoning. Techniques for summarizing, correlating, and interpreting log and metric data using AI. Real-world architecture for integrating Generative AI into operational pipelines (e.g., prompt templates, embeddings, RAG).
Speaker
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Kamal BishtDiscover Financial ServicesKamal Singh Bisht is a seasoned technologist with over 18 years of experience across observability, AI/ML, and cybersecurity. He has held senior engineering and leadership roles at organizations like JPMorgan Chase, Zillow, and Discover Financial Services, where he specialized in building intelligent, scalable platforms for analytics and infrastructure monitoring. Kamal’s expertise lies in bridging advanced machine learning techniques—including Generative AI and LLMs—with real-world production systems. His recent work focuses on automating root cause analysis and anomaly detection in large-scale IT environments using AI-driven observability architectures. He has completed master’s from Bangalore University and Post Graduate Program in Artificial Intelligence and Machine Learning from the University of Texas at Austin. Kamal is also the author of technical publications https://al-kindipublisher.com/index.php/jcsts/article/view/9558 https://eajournals.org/ejcsit/vol13-issue27-2025/conversational-finance-llm-powered-payment-assistant-architecture/ and is actively contributing to the advancement of AI in enterprise observability.